Domain 1: Databricks Lakehouse Platform (Questions 1–11)

Q1. A data engineering team needs to store raw event data in a format that supports ACID transactions, schema enforcement, and time travel queries. Which storage format should they use?

A) CSV
B) Parquet
C) Delta
D) Avro

Q2. In the medallion architecture, which layer is responsible for deduplication and data type casting?

A) Bronze
B) Silver
C) Gold
D) Platinum

Q3. A data engineer wants to run ad-hoc PySpark queries interactively while developing a new pipeline. Which cluster type is most appropriate?

A) Job cluster
B) All-purpose cluster
C) SQL Warehouse
D) Serverless SQL Warehouse

Q4. Which of the following is TRUE about DBFS (Databricks File System)?

A) DBFS is a physical file system installed on each cluster node
B) DBFS is an abstraction layer on top of cloud object storage
C) DBFS can only store Delta format files
D) DBFS provides stronger durability than the underlying cloud storage

Q5. A data engineer runs dbutils.secrets.get("scope", "api_key") and tries to print the result. What will be displayed?

A) The actual API key value
B) An encrypted version of the API key
C) [REDACTED]
D) An error because secrets cannot be retrieved in notebooks

Q6. Which cluster access mode is required for full Unity Catalog support with multiple users sharing the same cluster?

A) No Isolation Shared
B) Shared
C) High Concurrency (legacy)
D) Single Node

Q7. A Serverless SQL Warehouse differs from a Classic SQL Warehouse in that:

A) Serverless warehouses support Python and Scala in addition to SQL
B) Serverless warehouses start in seconds and scale instantly
C) Serverless warehouses cost less per DBU
D) Serverless warehouses do not support Unity Catalog

Q8. Which dbutils function is used to execute another notebook and share the execution context?

A) dbutils.notebook.run()
B) %run /path/to/notebook
C) dbutils.fs.run()

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